Predictive value of the prognostic nutritional index for the severity of coronavirus disease 2019

Abstract

Objectives: Malnutrition plays a critical role in the onset and progress of the coronavirus disease 2019 (COVID-19). The aim of the present study was to explore the association of the prognostic nutritional index (PNI) score with the severity of COVID-19 and its predictive value of the severe form of COVID-19.

Methods: Clinical data were collected from 122 patients infected with COVID-19 and hospitalized at the Sixth People's Hospital of Wenzhou, China, a specialized infectious hospital affiliated with the Wenzhou Central Hospital. PNI score was calculated as serum albumin (g/L) + 5 × total lymphocyte count (/nL).

Results: The study population consisted of 105 patients (86.1%) with a common form and 17 patients (13.9%) with a severe form of COVID-19. PNI score significantly decreased from patients with common to severe forms of COVID-19 (P = .029) regardless of sex, age range, and body mass index (BMI). After adjustment for sex, age, indexes of liver and renal function, C-reactive protein, and current smoking status, PNI scores remained independently and inversely associated with the severity of COVID-19 (odd ratio: 0.797; P = .030). A receiver operating characteristic analysis showed that PNI scores had a similar accuracy to predict severe forms of COVID-19 compared with its combination with sex, age, and BMI (P = .402). PNI < 49 was defined as the cutoff value to predict the severe form of COVID-19.

Conclusions: Poorer nutritional status predisposed patients infected with COVID-19 to its severe form. Independently associated with the severity of COVID-19, PNI score could serve as a simple, fast, and effective predictor among patients with different sex, age, and BMI.

Keywords: Coronavirus disease 2019; Prediction; Prognostic nutritional index; Severity.

Fig. 1

Interference of sex, age, and body mass index with the association between the prognostic nutritional index (PNI) and severity of coronavirus disease 2019 (COVID-19), showing that the associations of (A) sex with PNI did not interfere with association between severity of COVID-19 and PNI, (B) age range with PNI did not interfere with the association between severity of COVID-19 and PNI, and (C) body mass index category with PNI did not interfere with the association between severity of COVID-19 and PNI.

Fig. 2

Receiver operating characteristic analyses for the prediction of the severe form of coronavirus disease 2019 of (A) prognostic nutritional index (PNI) for prediction, and (B) the combination of sex, age, body mass index, and PNI for prediction. The area under the curve of PNI is similar to that of the combination of sex, age, body mass index, and PNI (P = .042).